code: def get_loss(loss_name: str, cfg: omegaconf.DictConfig):
      """Instantiate loss from configuration."""
      klass = {
          "l1": torch.nn.L1Loss,
          "l2": torch.nn.MSELoss,
          "mel": losses.MelSpectrogramL1Loss,
          "mrstft": losses.MRSTFTLoss,
          "msspec": losses.MultiScaleMelSpectrogramLoss,
          "sisnr": losses.SISNR,
      }[loss_name]
      kwargs = dict(getattr(cfg, loss_name))
      return klass(**kwargs)
  
imports: from enum import Enum
  import logging
  import typing
  import dora
  import flashy
  import omegaconf
  import torch
  from torch import nn
  from torch.optim import Optimizer
  from .base import StandardSolver
  from ..None import adversarial, data, losses, metrics, optim
  from ..utils.utils import dict_from_config, get_loader
label_desc: Use image node_id 6 for calling a global function with example usage: get_loss(loss_name, cfg) and returns: klass